The influence of age, sex and cardiorespiratory fitness on maximal fat oxidation rate
Bibliographic record
Abstract
Fat oxidation decreases with age, yet no studies have previously investigated if aging affects the maximal fat oxidation rate (MFO) during exercise in men and women differently. We hypothesized that increased age would be associated with a decline in MFO and this would be more pronounced in women due to menopause, compared with men. In this cross-sectional study design, 435 (247/188, male/female) subjects of varying ages performed a DXA scan, a submaximal graded exercise test and a maximal oxygen uptake test, to measure MFO and cardiorespiratory fitness (CRF) by indirect calorimetry. Subjects were stratified into 12 groups according to sex (male/female), age (<45, 45–55 and >55 years), CRF (below average and above average). Women aged <45 years had a higher MFO relative to fat free mass (FFM) (mg/min/kg) compared with men, regardless of CRF. However, there were no differences in MFO (mg/min/kg FFM) between men and women, in the groups aged between 45–55 and >55 years. In summary, we found that women aged <45 years display a higher MFO (mg/min/kg FFM) compared with men and that this sexual divergence is abolished after the age of 45 years. Novelty: Maximal fat oxidation rate is higher in young women compared with men. This sex-related difference is attenuated after the age of 45 years. Cardiorespiratory fitness does not influence this sex-related difference.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".